The probability of achieving sustained virological response with pegIFN-RBV therapy in HIV-HCV-coinfected patients can be reliably estimated prior to initiation of therapy using an index that includes 4 noninvasive parameters.

A state-of-the-art review of flow observability, estimation, and prediction problems in traffic networks is performed. Since mathematical optimization provides a general framework for all of them, an integrated approach is used to perform the analysis of these problems and consider them as different optimization problems whose data, variables, constraints, and objective functions are the main elements that characterize the problems proposed by different authors. For example, counted, scanned or “a priori” data are the most common data sources; conservation laws, flow nonnegativity, link capacity, flow definition, observation, flow propagation, and specific model requirements form the most common constraints; and least squares, likelihood, possible relative error, mean absolute relative error, and so forth constitute the bases for the objective functions or metrics. The high number of possible combinations of these elements justifies the existence of a wide collection of methods for analyzing static and dynamic situations.

In this article we deal with the probabilistic and physical consistency of traffic-related random vari

A Bayesian network model is developed, in which all the items or elements encountered when travelling a railway line, such as terrain

Despite being the main tool used nowadays to simulate the evolution of the climate system, the spatial resolution of the current global climate models (GCMs)-typically up to around a hundred kilometers-is still insufficient for most practical applications (see e.g., Doblas-Reyes et al., 2013 and references therein). To alleviate this limitation, statistical downscaling (SD) methods aim to build models linking a set of key large-scale predictors (e.g., geopotential or winds) with the target predictand (e.g., precipitation or temperature) over the area of interest (see e.g., von Storch et al., 1993). Under the perfect prognosis (PP) approach (